[BioC] barcode with custom CDF

[Matthew McCall]

Dario,

For the barcode implementations in BioC, I used > 10,000 arrays from
each platform. I doubt this amount of data is available for all 8 Affy
platforms you're using. If you don't mind giving me a brief overview
of your research goals for this project (not cc'ing the BioC mailing
list if you're more comfortable with that), I might be able to provide
some alternatives to a full barcode implementation.

Best,
Matt


On Tue, Mar 26, 2013 at 10:47 AM, Dario Greco <dario.greco at ki.se> wrote:
> Dear Matt,
> thanks a lot for the quick reply!
> i'm working on data from 8 homo sapiens affymetrix platforms re-annotated with brainarray cdf (ensembl gene).
> i can have access to relatively large computer clusters, so that is not worrying me.
> the most obvious question is probably concerning what volume of data from chipsets other than 133a and 133p2 i would need in order to generate meaningful estimations.
> thanks
> d
>
>
> On Mar 26, 2013, at 2:43 PM, Matthew McCall <mccallm at gmail.com> wrote:
>
>> Dario,
>>
>> Generating the barcode vectors (estimating the null distribution for
>> each probeset) typically isn't something one can run on a laptop. It
>> takes about 1-2 days running in parallel on about 20 nodes of a
>> computing cluster. If you have access to such resources, I'm happy to
>> help you create your own implementation. Is the custom CDF you're
>> using one of the Brain Array CDFs or something of your own design?
>>
>> Best,
>> Matt
>>
>>
>> On Tue, Mar 26, 2013 at 7:03 AM, Dario Greco [guest]
>> <guest at bioconductor.org> wrote:
>>>
>>> Dear BioC-ers,
>>>
>>> I would like to run the function 'barcode' on a set of CEL files preprocessed with a custom CDF.
>>> I am wondering if there is a quick way to generate the needed vectors (mu and tau for the unexpressed distribution) in the same way as the package frmaTools allows for the fRMA necessary vectors.
>>> I hope I am not posting about an issue already treated in this mailing list, but searching it produced no obvious hints.
>>>
>>> thanks a lot for your help and suggestions.
>>> cheers
>>> dario
>>>
>>>
>>>
>>> -- output of sessionInfo():
>>>
>>> sessionInfo()
>>> R version 2.15.3 (2013-03-01)
>>> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
>>>
>>> locale:
>>> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
>>>
>>> attached base packages:
>>> [1] stats     graphics  grDevices utils     datasets  methods   base
>>>
>>> other attached packages:
>>> [1] hgu133plus2barcodevecs_1.0.5 hgu133plus2frmavecs_1.1.12
>>> [3] hgu133abarcodevecs_1.0.5     hthgu133acdf_2.11.0
>>> [5] AnnotationDbi_1.20.7         affy_1.36.1
>>> [7] frma_1.10.0                  Biobase_2.18.0
>>> [9] BiocGenerics_0.4.0           BiocInstaller_1.8.3
>>>
>>> loaded via a namespace (and not attached):
>>> [1] affxparser_1.30.2     affyio_1.26.0         Biostrings_2.26.3
>>> [4] bit_1.1-10            codetools_0.2-8       DBI_0.2-5
>>> [7] ff_2.2-11             foreach_1.4.0         GenomicRanges_1.10.7
>>> [10] IRanges_1.16.6        iterators_1.0.6       MASS_7.3-23
>>> [13] oligo_1.22.0          oligoClasses_1.20.0   parallel_2.15.3
>>> [16] preprocessCore_1.20.0 RSQLite_0.11.2        splines_2.15.3
>>> [19] stats4_2.15.3         tools_2.15.3          zlibbioc_1.4.0
>>>>
>>>
>>> --
>>> Sent via the guest posting facility at bioconductor.org.
>>
>>
>>
>> --
>> Matthew N McCall, PhD
>> 112 Arvine Heights
>> Rochester, NY 14611
>> Cell: 202-222-5880
>



-- 
Matthew N McCall, PhD
112 Arvine Heights
Rochester, NY 14611
Cell: 202-222-5880